AI Catalog and Rates

accurate ai cost reporting depends on two things knowing exactly how each model is priced applying the prices you actually pay, not just public list prices amberflo’s ai catalog solves both what the ai catalog is the ai catalog is a continuously updated catalog of public pricing for thousands of ai models across 100+ providers it includes all major providers, including openai anthropic google aws bedrock azure ai etc the catalog is used automatically by amberflo’s rating engine to convert raw usage data into cost no setup is required to get started why this matters most organizations assume ai cost accuracy ends at token counting it does not different providers price the same model differently use different units of measure charge separately for input and output apply negotiated discounts that never show up in public pricing without a centralized pricing catalog and custom rates, your ai cost numbers are wrong what you can see in the ai catalog each catalog entry includes the full pricing context required for accurate rating model identity vendor where the model is accessed from for example, a model accessed via openai directly versus via aws bedrock or azure ai provider the company that owns or publishes the model like openai for gpt 5 model name including version or family mode such as chat, embeddings, image generation, audio, or other specialized modes billing units unit of charge tokens, seconds, images, pages, or other provider specific units input vs output differentiation separate pricing for input usage and output usage when applicable this is critical input and output costs often differ significantly and drive very different optimization decisions zero setup cost accuracy by default by default amberflo automatically applies public list pricing from the ai catalog all ai gateway usage is rated immediately cost appears in dashboards without any configuration this makes it possible to go from raw usage to accurate ai cost in minutes